Intelligence index
Outperforms 48% of compared models
o4 Mini
OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports tool use and demonstrates competitive reasoning and coding performance across benchmarks like AIME (99.5% with Python) and SWE-bench, outperforming its predecessor o3-mini and even approaching o3 in some domains.
Despite its smaller size, o4-mini exhibits high accuracy in STEM tasks, visual problem solving (e.g., MathVista, MMMU), and code editing. It is especially well-suited for high-throughput scenarios where latency or cost is critical. Thanks to its efficient architecture and refined reinforcement learning training, o4-mini can chain tools, generate structured outputs, and solve multi-step tasks with minimal delay—often in under a minute.
- Input / output price
- $1.1/$4.4per 1M tokens
- Context
- 200K
- Released
- 2025-04-16
Pricing
Artificial Analysis
Explore rankingsDesign Arena
Elo scores and win rates across design and agent tasks.
Category performance
1,000-1,500 EloModel Arena
Data Visualization
991Elo
Win rate 50%
UI Component
978Elo
Win rate 46.9%
Game Development
1003Elo
Win rate 50%
3D
851Elo
Win rate 34%
Code Categories
974Elo
Win rate 46.4%
Website
985Elo
Win rate 47.1%
Related Models
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- Max output
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- Context
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- Max output
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- Input
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- Cache read
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